Literature DB >> 35388267

Awareness and practice regarding use of digital devices and ocular health among Saudi adolescents.

Abdulrahman AlDarrab1.   

Abstract

PURPOSE: To review the knowledge of ocular health and practices of digital device usage among adolescent Saudi Arabia population.
METHODS: This cross-sectional web-based survey was conducted in 2021 at a university in central Saudi Arabia. We asked questions regarding demographics, knowledge related to computer vision syndrome (CVS), and the use of digital devices for participants' daily activities. The acceptable grades of knowledge ("excellent" and "good") and practice scores were associated with the determinants using the nonparametric method of analysis.
RESULTS: Of 521 participating students, knowledge about CVS and its relation to digital device usage were excellent in 41 students (7.9%), good in 161 (39%), poor in 300 (57.6%), and very poor in 19 (3.6%). Twenty-eight (5.4%) students scored an "excellent" grade on practices for digital device usage, 216 (41.4%) scored "good," and 277 (53.2%) scored "poor." The knowledge score median was 1.0 (interquartile range 1.0; 2.0), and the practice score median was 6.0 (4.0; 9.0). Health studies students had better knowledge than other students (P = 0.004). Smartphone users had worse knowledge than users of other devices (P = 0.017). Females (P < 0.001) and health studies students (P = 0.004) were significantly associated with acceptable practices of using digital devices.
CONCLUSIONS: Awareness of ocular health because of abuse of digital devices was poor among participating students. The practice of digital device use was not healthy and needed improvement through preventive measures and counseling. Copyright:
© 2022 Oman Ophthalmic Society.

Entities:  

Keywords:  Adolescent health; computer vision syndrome; digital devices; knowledge and practice

Year:  2022        PMID: 35388267      PMCID: PMC8979392          DOI: 10.4103/ojo.ojo_283_21

Source DB:  PubMed          Journal:  Oman J Ophthalmol        ISSN: 0974-620X


Introduction

Eye and vision-related problems due to prolonged use of computer, tablet, e-reader, and cell phone is called computer vision syndrome (CVS). Its rapidly increasing magnitude, especially in the younger population, is a public health challenge.[12] This is more of an occupational hazard for employers in information technology and radiology and for those compelled to work in front of a computer for long hours.[345] Excessive use of digital devices is a major risk factor for CVS.[6] The lockdown during the COVID-19 pandemic further accentuated the problem of CVS.[7] We recommend several preventive measures to reduce the risk of CVS and the progression of the condition. They include frequent breaks while working with digital devices, using the optimum distance between digital devices and the eye, ensuring an ideal angle for the viewing device, appropriate sitting arrangements, ambient lighting, and the use of lubricating eye drops.[89] To implement these preventive measures, awareness of the population, especially high-risk groups, needs improvement; and their attitudes and practices for using digital devices need to be studied and, if needed, altered. This will be possible if baseline information on awareness and current practices for using digital devices are known. The literature includes numerous studies in different areas to estimate levels of awareness and practices.[9101112131415] However, standard assessment tools are debatable, rendering comparison a challenge.[16] Therefore, we recommend baseline assessment in different study areas before implementing a public health approach to address this issue. Our university has a population of 25,000 students and is in a semiurban area of central Saudi Arabia.[17] To the best of our knowledge, no study has been done that focuses on the adolescent population during the COVID pandemic to assess the underlying causes of CVS. Our study estimated the level of awareness of CVS and causes and current practices using digital devices and their determinants among university students.

Methods

The institution's ethical committee approved this survey. It was conducted from June 2020 to August 2020, and all students at our university were invited to participate through department e-mails. Those providing informed written consent were included in the survey. All the ethical principles of the Declaration of Helsinki were strictly followed. To calculate the sample for the proposed survey, we assumed that the level of awareness of acceptable quality would be approximately 34.1% of a total population of 25,000 university students (12). To achieve a 95% confidence interval and 5% acceptable margin of error with a clustering effect of 1.5, we needed to survey 511 students. We used OpenEpi software to calculate a sample size for this cross-sectional survey.[18] We used a Google platform for this web-based survey. The questionnaire included demographic information such as gender, age, and department enrolment. There were three questions on knowledge related to CVS, the effect of using digital devices on ocular health, and following the 20-20-20 rule to avoid CVS. There were 11 questions on each student's practices using digital devices [Appendix 1]. For a correct answer, a score of 1 was awarded, and for an incorrect or “do not know” answer, a score of 0 was assigned. If the student's response was “never,” “occasionally,” “frequently,” or “always,” a score of 0–3 was assigned. The sum of knowledge-related responses and the sum of practice-related responses for each participant were graded as very poor, poor, good, and excellent. Scores of good and excellent were considered acceptable. The knowledge and practice score-based grades were associated with independent determinants such as gender, age, department, the main digital device used, and the purpose of device use. We used a Statistical Package for the Social Studies SPSS 25 (IBM, NY, USA to undertake univariate parametric analysis. For qualitative variables, we presented number and percentage proportions. For quantitative variables, we calculated the median and interquartile range. The group of acceptable versus poor knowledge and practices was validated by estimating the odds ratio, its 95% confidence interval, and two-sided P value. A P < 0.05 was considered statistically significant.
Appendix 1

Questionnaire for evaluating student perceived awareness and practice of digital device usage

Serial numberQuestions (close-ended)
P1Do you use glasses while using digital devices?
P2What position of device use you usually keep?
P3At viewing angle of the digital device screen, you maintain from the eye level?
P4Did you seek medical intervention for eye strain symptoms?
P5Do you use anti-glare screen on your digital device
P6Do you use protective glasses while working with digital devices?
P7Do you use lubricating eye drops while working on digital device?
P8Do you take regular breaks while working on DVT?
P9How often do you take breaks and try to lake at a far object?
P10How long are your breaks from the electronic device?
P11Do you use spectacles for your refractive error problem?
K1Do you know that looking at the screen of the electronic device for a long time causes eye problems?
K2Are you aware of computer vision syndrome? I
K3Are you aware of the 20.20.20 rule?

DVT: Digital visual terminals

Questionnaire for evaluating student perceived awareness and practice of digital device usage DVT: Digital visual terminals

Results

In this survey, a total of 521 students participated with a mean age of 21.8 ± 2.7 years. The profile is presented in Table 1. Gender and age group distribution were fair. Students in health studies programs and students without spectacles were one-third of the surveyed population.
Table 1

Profile of Saudi college students surveyed for awareness and practices for preventing computer vision syndrome related to usage of digital devices

Determinantsn (%)
Age group (years)
 <22261 (50.1)
 22 and more260 (49.9)
Gender
 Male293 (56.2)
 Female228 (43.8)
Faculty
 Health167 (32.1)
 Other354 (67.9)
Using visual aids
 Yes172 (33.0)
 No349 (67.0)
Profile of Saudi college students surveyed for awareness and practices for preventing computer vision syndrome related to usage of digital devices The median score for knowledge of CVS and relation to digital device use was 1.0 (IQR 1.0; 2.0). Figure 1 shows the level of awareness based on these scores. More than half of the students had poor knowledge of CVS. The participants with either acceptable or poor knowledge grades were associated with different independent determinants. Table 2 shows that students in health studies had better knowledge than other students (P = 0.004). Smartphone users had poorer knowledge than users of other devices (P = 0.017).
Figure 1

Distribution of surveyed college students by the grades of knowledge about computer vision syndrome related to usage of digital devices. The total score of knowledge related responses on comparison to the gold standard were grades in 25% percentile. Excellent ≥75% score, good = 51%–75% score, poor = 26%–50% score and very poor = 0–25 score

Table 2

Determinants of knowledge score grade of digital device use and computer vision syndrome among Saudi college students

SurveyedAcceptable knowledge (excellent + good), n (%)Poor knowledge (poor + very poor), n (%)OR and (95% CI), two-sided P
Total521202 (38.8)319 (61.2)
Gender
 Male293110 (37.5)183 (62.5)0.89 (0.62-1.7), 0.52
 Female22892 (40.4)136 (59.6)
Faculty
 Health16780 (47.9)87 (52.1)0.57 (0.39-0.83), 0.004
 Other354122 (34.5)232 (65.5)
Age group (years)
 <2226195 (36.4)166 (63.6)1.2 (0.86-1.74), 0.23
 22 and more260107 (41.2)153 (58.8)
Main digital device
 Smartphone438160 (36.5)278 (63.5)1.8 (1.1-2.9), 0.017
 Other8342 (50.6)41 (49.4)
Purpose
 Studies13458 (43.3)76 (56.7)χ2=2.76, df=2, P=0.097
 Social media301116 (38.5)185 (61.5)
 Other8628 (32.6)58 (67.4)
Using spectacles
 Yes17258 (33.7)114 (65.3)0.72 (0.5-1.1), 0.1
 No349144 (41.3)205 (58.7)

OR: Odds ratio, CI: Confidence interval, df: Degree of freedom

Distribution of surveyed college students by the grades of knowledge about computer vision syndrome related to usage of digital devices. The total score of knowledge related responses on comparison to the gold standard were grades in 25% percentile. Excellent ≥75% score, good = 51%–75% score, poor = 26%–50% score and very poor = 0–25 score Determinants of knowledge score grade of digital device use and computer vision syndrome among Saudi college students OR: Odds ratio, CI: Confidence interval, df: Degree of freedom The median practice score for digital device usage was 6.0 (4.0; 9.0). The grade of practice is shown in Figure 2, based on scores. More than half of the surveyed students did a poor job protecting their eyes from CVS while using their digital devices. The participants with either acceptable or poor practice grades were associated with different independent determinants. Table 3 shows that females (P < 0.001) and students in health studies (P = 0.004) were more significantly associated with acceptable practices for using digital devices.
Figure 2

Distribution of surveyed college students by grades of practices for preventing computer vision syndrome while using digital devices. The total score of Practice related responses on comparison to the gold standard were grades in 25% percentile. Excellent ≥75% score, good = 51%–75% score, poor = 26%–50% score and very poor = 0–25 score

Table 3

Determinants of practice score grade of digital device usage and computer vision syndrome among Saudi college students

DeterminantsSurveyedAcceptable practice (excellent + good), n (%)Poor practice, n (%)OR and (95% CI), two-sided P
Total521244 (46.8)277 (53.2)
Gender
 Male293109 (44.7)184 (66.4)2.45 (1.7-3.5), <0.001
 Female228135 (55.3)93 (33.6)
Faculty
 Health16761 (25.0)106 (38.3)1.86 (1.3-2.7), 0.001
 Other354183 (75.0)171 (61.7)
Age group (years)
 <22261129 (52.9)132 (47.7)1.2 (0.87-1.74), 0.23
 22 and more260115 (47.1)145 (52.3)
Main digital device
 Smartphone438205 (84.0)233 (84.1)0.99 (0.62-1.7), 0.97
 Other8339 (16.0)44 (15.9)
Purpose
 Studies13472 (29.5)62 (22.4)χ2=2.6, df=3, P=0.1
 Social media301135 (55.3)166 (59.9)
 Other8639 (15.2)49 (17.7)
Using spectacles
 Yes17258 (33.7)114 (66.3)0.86 (0.6-1.3), 0.43
 No349130 (37.2)219 (62.8)

OR: Odds ratio, CI: Confidence interval, Df: Degree of freedom

Distribution of surveyed college students by grades of practices for preventing computer vision syndrome while using digital devices. The total score of Practice related responses on comparison to the gold standard were grades in 25% percentile. Excellent ≥75% score, good = 51%–75% score, poor = 26%–50% score and very poor = 0–25 score Determinants of practice score grade of digital device usage and computer vision syndrome among Saudi college students OR: Odds ratio, CI: Confidence interval, Df: Degree of freedom

Discussion

Highlight of results

The awareness of and practices for using digital devices and preventing CVS were poor in more than half of the college students in the study. Health students had better knowledge than other students. Those using a smartphone as their main device had worse knowledge than users of other devices. The digital device usage norms showed better practices by females and health students than males and students in other departments.

Strength of the study

The study shows adolescents’ knowledge of CVS and practices using digital devices in a semiurban area of Saudi Arabia. Relatively less awareness and poor practices were reflected in a high prevalence of CVS in this population. The study findings indicate that urgent remedial actions are needed to improve knowledge and adopt better practices while using digital devices to prevent the progression of CVS.

Knowledge about computer vision syndrome

Knowledge of CVS in the study was poor in more than half of the surveyed students. This is better than the 82.7% with poor knowledge among IT professionals and college students in Karnataka, India, but similar to the knowledge noted in students in Kenya.[1319] In a study in Western India, nearly 23% of medical students had little knowledge of CVS and the norms of using digital visual terminals (DVTs).[12] This supports the need for urgent health promotion to improve knowledge among young populations to address CVS and its negative effects on human working capabilities.

Practice of using digital devices and eye health

There are several standard norms established to work with digital devices to reduce CVS. Among the studied population, the level of practice was also poor in more than half of the students surveyed. A study in Kenya showed that four in ten students also had poor practices while working with DVTs.[20] One explanation for these poor practices is the lockdown during the COVID pandemic because limited socialization and spending more time in isolation increased the use of DVTs as the only means of interacting with friends, teachers, and colleagues.[15] It will be interesting to assess practices of the same cohort after mobility restrictions are lifted.

Level of awareness for using digital devices

There is a difference in the level of awareness and practices for using DVTs among health studies students compared with those of other departments in our study. George et al. also noted average-level knowledge among as many as 70% of surveyed engineering students.[20] Even the staff working in a hospital had inadequate knowledge of CVS in Nepal.[21] This indicates that health promotion material to improve awareness and practices to prevent CVS should be target specific.

Devices and computer vision syndrome

Students using a smartphone as their primary digital device compared with other devices such as tablets, desktop computers, and laptops had poorer awareness and practices. This could be because of the ease of holding a smartphone in inappropriate positions, the angle of viewing, and ease of use in poor ambient light. While working on other devices, the user is often forced to sit in a workplace in which standard norms are followed regarding distances from digital devices, illumination, and larger fonts. Smartphones are used for a longer duration in a day than other devices, leading to poorer safety practices that result in a higher risk of CVS in people using smartphones more than other devices.[22]

Limitations

There were few limitations in our study. The study included participants of one university of central Saudi Arabia. The participants being computer literate may not represent population without such facilities (which is rare in KSA). Therefore, extrapolation of our study outcomes to the entire adult population of Saudi Arabia should be done with a caution. Environmental factors while using digital devices were not documented. Hence, known risk factors such as illumination, timing of working on digital devices impact of air conditioning in room could not be studied.

Conclusions

The positive impact of a structured teaching program was noted in improving awareness and digital device use among secondary school students.[14] Using personal protective measures and refractive corrections were recommended to the health staff in Nepal to reduce CVS by adopting healthy practices while using digital devices.[21] The level of knowledge also improved from 3% to 68.3% among medical coding trainees after they participated in video teaching programs.[23] These programs suggest some of the known and accepted measures to address CVS, including taking frequent breaks while working with digital devices, blinking while working, using the correct strength of computer eyewear, maintaining a standard distance between the visual display screen and the eye, following the 20-20-20 rule, having adequate lighting while working with digital devices, and using lubricating eye drops. We also suggested these interventions to students, and after these training sessions, students evaluated their impact on awareness and safety practices.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.
  15 in total

1.  Computer vision syndrome: a study of knowledge and practices in university students.

Authors:  S C Reddy; C K Low; Y P Lim; L L Low; F Mardina; M P Nursaleha
Journal:  Nepal J Ophthalmol       Date:  2013 Jul-Dec

Review 2.  Computer Vision Syndrome.

Authors:  Susan A Randolph
Journal:  Workplace Health Saf       Date:  2017-07       Impact factor: 1.413

3.  A reliable and valid questionnaire was developed to measure computer vision syndrome at the workplace.

Authors:  María del Mar Seguí; Julio Cabrero-García; Ana Crespo; José Verdú; Elena Ronda
Journal:  J Clin Epidemiol       Date:  2015-01-28       Impact factor: 6.437

Review 4.  Computer Vision Syndrome: Darkness Under the Shadow of Light.

Authors:  Ashish Chawla; Tze Chwan Lim; Sumer N Shikhare; Peter L Munk; Wilfred C G Peh
Journal:  Can Assoc Radiol J       Date:  2019-02       Impact factor: 2.248

5.  Prevalence of Self-Reported Symptoms of Computer Vision Syndrome and Associated Risk Factors among School Students in China during the COVID-19 Pandemic.

Authors:  Rui Li; Bowen Ying; Yingxiao Qian; Danni Chen; Xiaoxiao Li; Hui Zhu; Hu Liu
Journal:  Ophthalmic Epidemiol       Date:  2021-08-25

Review 6.  Ocular and visual discomfort associated with smartphones, tablets and computers: what we do and do not know.

Authors:  Sukanya Jaiswal; Lisa Asper; Jennifer Long; Abigail Lee; Kirsten Harrison; Blanka Golebiowski
Journal:  Clin Exp Optom       Date:  2019-01-21       Impact factor: 2.742

7.  Computer vision syndrome and its associated ergonomic factors among bank workers.

Authors:  Samuel Bert Boadi-Kusi; Peter Osei-Wusu Adueming; Francisca Ama Hammond; Ebenezer Oduro Antiri
Journal:  Int J Occup Saf Ergon       Date:  2021-04-05

8.  Computer vision syndrome among computer office workers in a developing country: an evaluation of prevalence and risk factors.

Authors:  P Ranasinghe; W S Wathurapatha; Y S Perera; D A Lamabadusuriya; S Kulatunga; N Jayawardana; P Katulanda
Journal:  BMC Res Notes       Date:  2016-03-09

9.  Computer vision syndrome prevalence, knowledge and associated factors among Saudi Arabia University Students: Is it a serious problem?

Authors:  Sultan H Al Rashidi; H Alhumaidan
Journal:  Int J Health Sci (Qassim)       Date:  2017 Nov-Dec

Review 10.  The Impact of Internet and Videogaming Addiction on Adolescent Vision: A Review of the Literature.

Authors:  Ioanna Mylona; Emmanouil S Deres; Georgianna-Despoina S Dere; Ioannis Tsinopoulos; Mikes Glynatsis
Journal:  Front Public Health       Date:  2020-03-05
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.